Processing of audio data in multi-speaker multi-channel environments

A method comprising:

• generating a plurality of embeddings associated with a set of audio data channels (ADCs), the set of ADCs jointly capturing a speech produced by one or more speakers;
• processing, using one or more neural network (NN) models, the plurality of embeddings to obtain one or more aggregated embeddings, individual aggregated embeddings obtained by aggregating a subset of the plurality of embeddings, the subset selected, for individual temporal units of the speech, based on similarity of the plurality of embeddings associated with said individual temporal units of the speech;
• and
• processing, using an audio processing NN model, the one or more aggregated embeddings to obtain an association of the speech to the one or more speakers.

A system comprising:

• one or more processing units to:
• obtain a first set of embeddings, each embedding of the first set of embeddings associated with (i) a respective audio data channel (ADC) of a set of ADCs jointly capturing speech produced by one or more speakers and (ii) a respective time frame of a plurality of time frames;
• process the first set of embeddings to identify, for individual time frames of the plurality of time frames, a subset of embeddings from the first set based at least on similarity among the first set of embeddings;
• obtain a second set of embeddings, each embedding of the second set of embeddings obtained by combining embeddings of the subset associated with a corresponding time frame;
• and
• process, using an audio processing neural network (NN) model, the second set of embeddings to obtain an association of the speech to the one or more speakers.